Kafka Streams实战：构建实时应用与微服务

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《Manning.Kafka.Streams.in.Action.2018.8》是一本专为IT专业人士撰写的实战指南，由William P. Bejeck Jr. 执笔，Neha Narkeade担任序言作者。本书聚焦于实时应用和微服务开发，利用Kafka Streams API进行构建。Kafka Streams是Apache Kafka项目的一部分，它提供了一种在分布式流处理环境中处理数据的强大工具，特别适合于实时数据流的处理和分析。书中涵盖了以下关键知识点： 1. **实时应用与微服务**：本书介绍了如何使用Kafka Streams API来构建实时应用程序，这些应用能够处理不断流动的数据，并在微服务架构中发挥重要作用。通过实时处理，系统能够对事件做出快速反应，提高业务响应速度和用户体验。 2. **Kafka Streams API**：Kafka Streams API允许开发者创建声明式、无状态或有状态的处理管道，处理来自Kafka主题的数据。API提供了一系列内置的处理器（processors），如Filtering、Select-key等，用于执行复杂的数据转换和聚合操作。 3. **源和sink模式**：书中的内容包括如何定义数据的输入源（sources）和输出目的地（sinks），例如电子商店和咖啡馆的事务流，以及用户购买、积分奖励等业务逻辑的处理。 4. **处理器设计**：书中详细探讨了各种处理器的使用，如Cafe和Electronics处理器可能用于处理特定主题的数据，而Rewards处理器则可能涉及积分计算。每个处理器都是实现业务逻辑的关键组件。 5. **分支处理**：在实时处理场景中，可能会遇到需要基于条件或规则进行分支处理的情况，这在处理复杂的数据流时是必不可少的。 6. **实践案例和最佳实践**：书中包含了大量的实例和最佳实践，帮助读者理解如何在实际项目中有效地应用Kafka Streams API，确保系统的稳定性和性能。 7. **版权和购买信息**：这本书受到版权保护，未经Manning Publications Co. 的许可，不得擅自复制或传播。对于购买和查询更多信息，读者可以通过Manning官网获取折扣和联系出版社的特殊销售部门。《Manning.Kafka.Streams.in.Action.2018.8》是一本实用的教程，旨在帮助读者掌握Kafka Streams在实时应用和微服务场景中的应用技巧，无论是初学者还是经验丰富的开发人员，都能从中获得有价值的知识和实践经验。

xiv

acknowledgments

First and foremost, I’d like to thank my wife Beth and acknowledge all the support I

received from her during this process. Writing a book is a time-consuming task, and

without her encouragement, this book never would have happened. Beth, you are fan-

tastic, and I’m very grateful to have you as my wife. I’d also like to acknowledge my

children, who put up with Dad sitting in his office all day on most weekends and

accepted the vague answer “Soon” when they asked when I’d be finished writing.

Next, I thank Guozhang Wang, Matthias Sax, Damian Guy, and Eno Thereska, the

core developers of Kafka Streams. Without their brilliant insights and hard work,

there would be no Kafka Streams, and I wouldn’t have had the chance to write about

this game-changing tool.

I thank my editor at Manning, Frances Lefkowitz, whose expert guidance and

infinite patience made writing a book almost fun. I also thank John Hyaduck for his

spot-on technical feedback, and Valentin Crettaz, the technical proofer, for his excel-

lent work reviewing the code. Additionally, I thank the reviewers for their hard work

and invaluable feedback in making the quality of this book better for all readers:

Alexander Koutmos, Bojan Djurkovic, Dylan Scott, Hamish Dickson, James Frohnhofer,

Jim Manthely, Jose San Leandro, Kerry Koitzsch, László Hegedüs, Matt Belanger,

Michele Adduci, Nicholas Whitehead, Ricardo Jorge Pereira Mano, Robin Coe, Sumant

Tambe, and Venkata Marrapu.

Finally, I’d like to acknowledge all the Kafka developers for building such high-

quality software, especially Jay Kreps, Neha Narkhede, and Jun Rao—not just for start-

ing Kafka in the first place, but also for founding Confluent, a great and inspiring

place to work.

ABOUT THIS BOOK

xvi

How this book is organized: a roadmap

This book has four parts spread over nine chapters. Part 1 introduces a mental model

of Kafka Streams to show you the big-picture view of how it works. These chapters also

provide the basics of Kafka, for those who need them or want a review:

■

Chapter 1 provides some history of how and why stream processing became

necessary for handling real-time data at scale. It also presents the mental model

of Kafka Streams. I don’t go over any code but rather describe how Kafka

Streams works.

■

Chapter 2 is a primer for developers who are new to Kafka. Those with more

experience with Kafka can skip this chapter and get right into Kafka Streams.

Part 2 moves on to Kafka Streams, starting with the basics of the API and continuing

to the more complex features:

■

Chapter 3 presents a Hello World application and then presents a more realistic

example: developing an application for a fictional retailer, including advanced

features.

■

Chapter 4 discusses state and explains how it’s sometimes required for stream-

ing applications. You’ll learn about state store implementations and how to per-

form joins in Kafka Streams.

■

Chapter 5 explores the duality of tables and streams, and introduces a new con-

cept: the

KTable

. Whereas a

KStream

is a stream of events, a

KTable

is a stream

of related events or an update stream.

■

Chapter 6 goes into the low-level Processor API. Up to this point, you’ve been

working with the high-level DSL, but here you’ll learn how to use the Processor

API when you need to write customized parts of an application.

Part 3 moves on from developing Kafka Streams applications to managing Kafka

Streams:

■

Chapter 7 explains how to test a Kafka Streams application. You’ll learn how to

test an entire topology, unit-test a single processor, and use an embedded Kafka

broker for integration tests.

■

Chapter 8 covers how to monitor your Kafka Streams application, both to see

how long it takes to process records and to locate potential processing bottle-

necks.

Part 4 is the capstone of the book, where you’ll delve into advanced application devel-

opment with Kafka Streams:

■

Chapter 9 covers integrating existing data sources into Kafka Streams using

Kafka Connect. You’ll learn to include database tables in a streaming applica-

tion. Then, you’ll see how to use interactive queries to provide visualization

and dashboard applications while data is flowing through Kafka Streams, with-

out the need for relational databases. The chapter also introduces KSQL,

ABOUT THIS BOOK

xvii

which you can use to run continuous queries over Kafka without writing any

code, by using SQL.

About the code

This book contains many examples of source code both in numbered listings and

inline with normal text. In both cases, source code is formatted in a

fixed-width

font

this

to separate it from ordinary text.

In many cases, the original source code has been reformatted; we’ve added line

breaks and reworked indentation to accommodate the available page space in the

book. In rare cases, even this was not enough, and listings include line-continuation

markers (

➥

). Additionally, comments in the source code have often been removed

from the listings when the code is described in the text. Code annotations accompany

many of the listings, highlighting important concepts.

Finally, it’s important to note that many of the code examples aren’t meant to

stand on their own: they’re excerpts containing only the most relevant parts of what is

currently under discussion. You’ll find all the examples from the book in the accom-

panying source code in their complete form. Source code for the book’s examples is

available from GitHub at https://github.com/bbejeck/kafka-streams-in-action and

the publisher’s website at www.manning.com/books/kafka-streams-in-action.

The source code for the book is an all-encompassing project using the build tool

Gradle (https://gradle.org). You can import the project into either IntelliJ or Eclipse

using the appropriate commands. Full instructions for using and navigating the source

code can be found in the accompanying README.md file.

Book forum

Purchase of Kafka Streams in Action includes free access to a private web forum run by

Manning Publications where you can make comments about the book, ask technical

questions, and receive help from the author and from other users. To access the

forum, go to https://forums.manning.com/forums/kafka-streams-in-action. You can

also learn more about Manning’s forums and the rules of conduct at https://forums

.manning.com/forums/about.

Manning’s commitment to our readers is to provide a venue where a meaningful

dialogue between individual readers and between readers and the author can take

place. It is not a commitment to any specific amount of participation on the part of

the author, whose contribution to the forum remains voluntary (and unpaid). We sug-

gest you try asking him some challenging questions lest his interest stray! The forum

and the archives of previous discussions will be accessible from the publisher’s website

as long as the book is in print.

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